from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
reporting = HpMatchReporting(against_lib="onnx", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time onnx. For instance, a speedup of 2 means that onnx is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 2.345982 | 0.197174 | NaN | ... | brute | -1 | 1 | 0.663 | 0.351551 | 0.008051 | 1.000 | 6.673228 | 6.674977 | 0.337 |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | e70d8e7886766d41f30889506baa1e67 | 2cf49829391aa7891e877f2ed070adf0 | 0.027585 | 0.003773 | NaN | ... | brute | -1 | 1 | 1.000 | 18.881258 | 0.082581 | 0.757 | 0.001461 | 0.001461 | 0.243 |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 22d5eac4a4146149b35eae6914921514 | 2cf49829391aa7891e877f2ed070adf0 | 3.136109 | 0.100838 | NaN | ... | brute | -1 | 5 | 0.757 | 18.757458 | 0.110708 | 0.882 | 0.167193 | 0.167196 | 0.125 |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 2.443875 | 0.027407 | NaN | ... | brute | 1 | 100 | 0.882 | 0.344548 | 0.008601 | 1.000 | 7.092985 | 7.095194 | 0.118 |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 16f94fc93942ff7ece860c9b0f64645f | 2cf49829391aa7891e877f2ed070adf0 | 0.025788 | 0.002638 | NaN | ... | brute | 1 | 100 | 1.000 | 18.873383 | 0.101548 | 0.757 | 0.001366 | 0.001366 | 0.243 |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2d5f2b2c02d77766434d9e5033b4a76c | 2cf49829391aa7891e877f2ed070adf0 | 3.139071 | 0.062996 | NaN | ... | brute | -1 | 100 | 0.882 | 19.419744 | 0.041208 | 0.663 | 0.161643 | 0.161644 | 0.219 |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 2.442894 | 0.022442 | NaN | ... | brute | 1 | 5 | 0.757 | 0.284448 | 0.009618 | 1.000 | 8.588180 | 8.593088 | 0.243 |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | efac583623711d395ddae7a1e881ff68 | 2cf49829391aa7891e877f2ed070adf0 | 0.026557 | 0.001892 | NaN | ... | brute | 1 | 5 | 1.000 | 4.268789 | 0.081962 | 0.922 | 0.006221 | 0.006222 | 0.078 |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | b79d63bb7670c492de5c3befac58fe29 | 2cf49829391aa7891e877f2ed070adf0 | 1.621578 | 0.010942 | NaN | ... | brute | 1 | 1 | 0.663 | 4.254634 | 0.047411 | 0.929 | 0.381132 | 0.381156 | 0.266 |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 1.851052 | 0.028637 | NaN | ... | brute | -1 | 1 | 0.896 | 0.270214 | 0.008247 | 1.000 | 6.850320 | 6.853510 | 0.104 |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | e70d8e7886766d41f30889506baa1e67 | 88843f54689e3271092f70126e1de585 | 0.005521 | 0.001625 | NaN | ... | brute | -1 | 1 | 1.000 | 4.374117 | 0.123455 | 0.922 | 0.001262 | 0.001263 | 0.078 |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 22d5eac4a4146149b35eae6914921514 | 88843f54689e3271092f70126e1de585 | 2.809051 | 0.070351 | NaN | ... | brute | -1 | 5 | 0.922 | 4.355370 | 0.067786 | 0.896 | 0.644963 | 0.645041 | 0.026 |
12 rows × 22 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.001 | 5.744 | 0.0 | -1 | 1 | 19.253 | 0.126 | 0.663 | 0.001 | 0.001 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.013 | 0.001 | 5.935 | 0.0 | -1 | 5 | 0.354 | 0.014 | 1.000 | 0.038 | 0.038 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.000 | 5.890 | 0.0 | 1 | 100 | 18.638 | 0.238 | 0.882 | 0.001 | 0.001 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.001 | 5.652 | 0.0 | -1 | 100 | 0.366 | 0.021 | 1.000 | 0.039 | 0.039 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.001 | 5.914 | 0.0 | 1 | 5 | 4.372 | 0.123 | 0.896 | 0.003 | 0.003 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.015 | 0.001 | 5.358 | 0.0 | 1 | 1 | 0.268 | 0.008 | 1.000 | 0.056 | 0.056 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.314 | 0.0 | -1 | 1 | 4.262 | 0.064 | 0.929 | 0.001 | 0.001 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.005 | 0.000 | 0.326 | 0.0 | -1 | 5 | 0.278 | 0.005 | 1.000 | 0.018 | 0.018 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.346 | 0.197 | 0.0 | 0.002 | -1 | 1 | 0.352 | 0.008 | 1.000 | 6.673 | 6.675 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.028 | 0.004 | 0.0 | 0.028 | -1 | 1 | 18.881 | 0.083 | 0.757 | 0.001 | 0.001 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.136 | 0.101 | 0.0 | 0.003 | -1 | 5 | 18.757 | 0.111 | 0.882 | 0.167 | 0.167 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.027 | 0.003 | 0.0 | 0.027 | -1 | 5 | 0.352 | 0.011 | 1.000 | 0.077 | 0.078 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.444 | 0.027 | 0.0 | 0.002 | 1 | 100 | 0.345 | 0.009 | 1.000 | 7.093 | 7.095 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.026 | 0.003 | 0.0 | 0.026 | 1 | 100 | 18.873 | 0.102 | 0.757 | 0.001 | 0.001 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 3.139 | 0.063 | 0.0 | 0.003 | -1 | 100 | 19.420 | 0.041 | 0.663 | 0.162 | 0.162 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.029 | 0.003 | 0.0 | 0.029 | -1 | 100 | 0.363 | 0.009 | 1.000 | 0.079 | 0.079 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.443 | 0.022 | 0.0 | 0.002 | 1 | 5 | 0.284 | 0.010 | 1.000 | 8.588 | 8.593 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.027 | 0.002 | 0.0 | 0.027 | 1 | 5 | 4.269 | 0.082 | 0.922 | 0.006 | 0.006 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.622 | 0.011 | 0.0 | 0.002 | 1 | 1 | 4.255 | 0.047 | 0.929 | 0.381 | 0.381 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.024 | 0.001 | 0.0 | 0.024 | 1 | 1 | 0.267 | 0.008 | 1.000 | 0.091 | 0.091 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.851 | 0.029 | 0.0 | 0.002 | -1 | 1 | 0.270 | 0.008 | 1.000 | 6.850 | 6.854 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.002 | 0.0 | 0.006 | -1 | 1 | 4.374 | 0.123 | 0.922 | 0.001 | 0.001 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.809 | 0.070 | 0.0 | 0.003 | -1 | 5 | 4.355 | 0.068 | 0.896 | 0.645 | 0.645 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.002 | 0.0 | 0.007 | -1 | 5 | 0.269 | 0.008 | 1.000 | 0.026 | 0.026 | See | See |
KNeighborsClassifier_kd_tree¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.920315 | 1.186926 | NaN | ... | kd_tree | -1 | 1 | 0.929 | 2.917273 | 0.272286 | 1.000 | 0.315471 | 0.316842 | 0.071 |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | fe8267e25dadb302ed498e50fabf7ef4 | 1eb6cf1a720a225efb91df0b529b0510 | 0.003030 | 0.000589 | NaN | ... | kd_tree | -1 | 1 | 1.000 | 143.781297 | 0.000000 | 0.946 | 0.000021 | 0.000021 | 0.054 |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | dc74b969bf622bc24ba3bc62c980983b | 1eb6cf1a720a225efb91df0b529b0510 | 1.125627 | 0.559873 | NaN | ... | kd_tree | -1 | 5 | 0.946 | 143.639217 | 0.000000 | 0.951 | 0.007836 | 0.007836 | 0.005 |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 6.058615 | 0.722357 | NaN | ... | kd_tree | 1 | 100 | 0.951 | 3.033202 | 0.199385 | 1.000 | 1.997432 | 2.001743 | 0.049 |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 41accfcdcd5c50784bedf6164b63de99 | 1eb6cf1a720a225efb91df0b529b0510 | 0.003938 | 0.001777 | NaN | ... | kd_tree | 1 | 100 | 1.000 | 145.110898 | 0.000000 | 0.946 | 0.000027 | 0.000027 | 0.054 |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 022f7445d43bb1dbc24dc3106c03cb93 | 1eb6cf1a720a225efb91df0b529b0510 | 3.511473 | 0.341730 | NaN | ... | kd_tree | -1 | 100 | 0.951 | 142.911426 | 0.000000 | 0.929 | 0.024571 | 0.024571 | 0.022 |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 1.879582 | 0.409067 | NaN | ... | kd_tree | 1 | 5 | 0.946 | 0.006562 | 0.000285 | 1.000 | 286.413569 | 286.683871 | 0.054 |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 84622ba45e941db642965553529e1941 | 1eb6cf1a720a225efb91df0b529b0510 | 0.001771 | 0.000448 | NaN | ... | kd_tree | 1 | 5 | 1.000 | 0.047423 | 0.002399 | 0.911 | 0.037341 | 0.037389 | 0.089 |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | a9455565db1d8e052a783317c99744ff | 1eb6cf1a720a225efb91df0b529b0510 | 1.018047 | 0.382193 | NaN | ... | kd_tree | 1 | 1 | 0.929 | 0.069796 | 0.003577 | 0.894 | 14.585944 | 14.605084 | 0.035 |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.038381 | 0.016261 | NaN | ... | kd_tree | -1 | 1 | 0.891 | 0.006373 | 0.000641 | 1.000 | 6.022782 | 6.053193 | 0.109 |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | fe8267e25dadb302ed498e50fabf7ef4 | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.004434 | 0.001514 | NaN | ... | kd_tree | -1 | 1 | 1.000 | 0.049109 | 0.005837 | 0.911 | 0.090287 | 0.090922 | 0.089 |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | dc74b969bf622bc24ba3bc62c980983b | edf7cb014c2c0910e1c3aaaf8ae633f2 | 0.034384 | 0.001957 | NaN | ... | kd_tree | -1 | 5 | 0.911 | 0.044800 | 0.002006 | 0.891 | 0.767518 | 0.768287 | 0.020 |
12 rows × 22 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.844 | 0.034 | 0.028 | 0.0 | -1 | 1 | 141.107 | 0.000 | 0.929 | 0.020 | 0.020 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.907 | 0.115 | 0.020 | 0.0 | -1 | 5 | 3.098 | 0.290 | 1.000 | 1.261 | 1.267 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.972 | 0.119 | 0.020 | 0.0 | 1 | 100 | 148.515 | 0.000 | 0.951 | 0.027 | 0.027 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.920 | 0.089 | 0.020 | 0.0 | -1 | 100 | 3.108 | 0.274 | 1.000 | 1.261 | 1.266 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.037 | 0.095 | 0.020 | 0.0 | 1 | 5 | 0.046 | 0.002 | 0.891 | 87.903 | 87.967 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.973 | 0.100 | 0.020 | 0.0 | 1 | 1 | 0.006 | 0.000 | 1.000 | 687.569 | 688.424 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.016 | 0.0 | -1 | 1 | 0.069 | 0.002 | 0.894 | 0.015 | 0.015 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.021 | 0.0 | -1 | 5 | 0.006 | 0.000 | 1.000 | 0.123 | 0.123 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.920 | 1.187 | 0.0 | 0.001 | -1 | 1 | 2.917 | 0.272 | 1.000 | 0.315 | 0.317 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.0 | 0.003 | -1 | 1 | 143.781 | 0.000 | 0.946 | 0.000 | 0.000 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.126 | 0.560 | 0.0 | 0.001 | -1 | 5 | 143.639 | 0.000 | 0.951 | 0.008 | 0.008 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.000 | 0.0 | 0.004 | -1 | 5 | 2.933 | 0.231 | 1.000 | 0.001 | 0.001 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 6.059 | 0.722 | 0.0 | 0.006 | 1 | 100 | 3.033 | 0.199 | 1.000 | 1.997 | 2.002 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.002 | 0.0 | 0.004 | 1 | 100 | 145.111 | 0.000 | 0.946 | 0.000 | 0.000 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.511 | 0.342 | 0.0 | 0.004 | -1 | 100 | 142.911 | 0.000 | 0.929 | 0.025 | 0.025 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.006 | 0.001 | 0.0 | 0.006 | -1 | 100 | 3.129 | 0.267 | 1.000 | 0.002 | 0.002 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.880 | 0.409 | 0.0 | 0.002 | 1 | 5 | 0.007 | 0.000 | 1.000 | 286.414 | 286.684 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.0 | 0.002 | 1 | 5 | 0.047 | 0.002 | 0.911 | 0.037 | 0.037 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.018 | 0.382 | 0.0 | 0.001 | 1 | 1 | 0.070 | 0.004 | 0.894 | 14.586 | 14.605 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.0 | 0.001 | 1 | 1 | 0.006 | 0.001 | 1.000 | 0.198 | 0.199 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.038 | 0.016 | 0.0 | 0.000 | -1 | 1 | 0.006 | 0.001 | 1.000 | 6.023 | 6.053 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.004 | 0.002 | 0.0 | 0.004 | -1 | 1 | 0.049 | 0.006 | 0.911 | 0.090 | 0.091 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.034 | 0.002 | 0.0 | 0.000 | -1 | 5 | 0.045 | 0.002 | 0.891 | 0.768 | 0.768 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.003 | 0.000 | 0.0 | 0.003 | -1 | 5 | 0.006 | 0.001 | 1.000 | 0.432 | 0.435 | See | See |
HistGradientBoostingClassifier_best¶onnx (1.10.1) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: learning_rate=0.01, n_iter_no_change=10.0, max_leaf_nodes=100.0, max_bins=255.0, min_samples_leaf=100.0, max_iter=300.0.
| estimator | function | n_samples_train | n_samples | n_features | parameters_digest | dataset_digest | mean_duration_sklearn | std_duration_sklearn | n_iter | ... | max_leaf_nodes | min_samples_leaf | n_iter_no_change | accuracy_score_sklearn | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | diff_accuracy_scores | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 25b9f14bed7dd5d830c6ccd4dfebbf0c | 8c8fffa8ec4b2d8de833421f9e32beab | 0.193181 | 0.004653 | 300 | ... | 100 | 100 | 10 | 0.824 | 0.494395 | 0.008458 | 1.0 | 0.390743 | 0.3908 | 0.176 |
1 rows × 25 columns
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | HistGradientBoostingClassifier_best | fit | 100000 | 100000 | 100 | 128.674 | 0.0 | 300 | 0.001 | 0.001 | 0.6 | 0.058 | 0.824 | 214.629 | 215.625 | See | See |
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_onnx | std_duration_onnx | accuracy_score_onnx | speedup | std_speedup | sklearn_profiling | onnx_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | HistGradientBoostingClassifier_best | predict | 100000 | 1000 | 100 | 0.193 | 0.005 | 300 | 0.004 | 0.0 | 0.494 | 0.008 | 1.0 | 0.391 | 0.391 | See | See |